FuseFISH: Robust Detection of Transcribed Gene Fusions in Single Cells
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Semrau-2014-FuseFISH_ Robust Det.pdf
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Author(s)
Semrau, Stefan
Crosetto, Nicola
Bienko, Magda
Boni, Marina
Bernasconi, Paolo
Chiarle, Roberto
van Oudenaarden, Alexander
van Oudenaarden, Alexander
Date Issued
December 2013
Journal
Cell Reports
Publisher
Elsevier
Citation
Semrau, Stefan, Nicola Crosetto, Magda Bienko, Marina Boni, Paolo Bernasconi, Roberto Chiarle, and Alexander van Oudenaarden. “FuseFISH: Robust Detection of Transcribed Gene Fusions in Single Cells.” Cell Reports 6, no. 1 (January 2014): 18–23.
Version
Final published version
Abstract
Transcribed gene fusions are key biomarkers in many hematologic and solid tumors, often representing the primary oncogenic driver mutation. Here, we report an experimental and computational pipeline for detecting fusion transcripts using single-molecule RNA FISH and unbiased correlation analysis (FuseFISH). We constructed a genome-wide database of optimal oligonucleotide sequences, enabling quick design of FuseFISH probes against known and novel fusions. We implemented FuseFISH in cell lines, tissue sections, and purified RNA, reliably detecting one BCR-ABL1 positive in 10,000 negative cells. In 34 hematologic samples, we detected BCR-ABL1 transcripts with high specificity and sensitivity. Finally, we measured BCR-ABL1 expression heterogeneity and dynamics in single CML cells exposed to the kinase inhibitor Nilotinib. Our resource and methods are ideal for streamlined validation of fusions newly identified by next-generation sequencing, and they pave the way to studying the impact of fusion expression variability on clinical outcome.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Physics
Koch Institute for Integrative Cancer Research at MIT
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DOI of Published Version
https://doi.org/10.1016/j.celrep.2013.12.002
